The evaluation protocol is the same as in prior work [1]}. A perturbed ground-truth object pose is used for initialization. The perturbation adds a uniformly sampled random translation within a 4cm range to evaluate robustness against a noisy initial pose [1]}. No re-initialization is allowed during tracking. To evaluate robustness against missing frames, the same uniformly sampled 450 frames out of 3200 in the testing videos are dropped [1]}. Four metrics are adopted: 1) 55cm: percentage of estimates with orientation error < 5and translation error < 5cm - the higher the better; 2) IoU25 (Intersection over Union): percentage of cases where the overlapping prediction and ground-truth 3D bounding box volume is larger than 25% of their union - the higher the better; 3) Rerr: mean orientation error in degrees - the lower the better; and 4) Terr: mean translation error in centimeters - the lower the better. For Rerr and Terr, estimates with IoU\(\le \) 25 are not counted when computing averageshttps://github.com/j96w/6-PACK/blob/master/benchmark.py [1]}.
